Self-organized phase transitions in neural networks as a neural mechanism of information processing.

Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on the Hebbian learning rule are the driving force for the transition. The phase transition between the following two dynamical stable states is studied in detail, the state where the firing pattern is changed temporally so as to itinerate among several patterns and the state where the firing pattern is fixed to one of several patterns. The phase transition from the pattern itinerant state to a pattern fixed state may be induced by the Hebbian learning process under a weak input relevant to the fixed pattern. The reverse transition may be induced by the Hebbian unlearning process without input. The former transition is considered as recognition of the input stimulus, while the latter is considered as clearing of the used input data to get ready for new input. To ensure that information processing based on the phase transition can be made by the infinitesimal and short-term synaptic changes, it is absolutely necessary that the network always stays near the critical state corresponding to the phase transition point.

A general proposal to multilingual information access based on syntactic-semantic patterns

In the last few years, there has been a wide development in the research on textual information systems. The goal is to improve these systems in order to allow an easy localization, treatment and access to the information stored in digital format (Digital Databases, Documental Databases, and so on). There are lots of applications focused on information access (for example, Web-search systems like Google or Altavista). However, these applications have problems when they must access to cross-language information, or when they need to show information in a language different from the one of the query. This paper explores the use of syntactic-sematic patterns as a method to access to multilingual information, and revise, in the case of Information Retrieval, where it is possible and useful to employ patterns when it comes to the multilingual and interactive aspects. On the one hand, the multilingual aspects that are going to be studied are the ones related to the access to documents in different languages from the one of the query, as well as the automatic translation of the document, i.e. a machine translation system based on patterns. On the other hand, this paper is going to go deep into the interactive aspects related to the reformulation of a query based on the syntactic-semantic pattern of the request.

Molecules, wing pattern and distribution: an approach to species delimitation in the "loxurina group" (Lepidoptera: Lycaenidae: Penaincisalia)

The wide range of morphological variations in the “loxurina group” makes taxa identification difficult, and despite several reviews, serious taxonomical confusion remains. We make use of DNA data in conjunction with morphological appearance and available information on species distribution to delimit the boundaries of the “loxurina” group species previously established based on morphology. A fragment of 635 base pairs within the mtDNA gene cytochrome oxidase I (COI) was analysed for seven species of the “loxurina group”. Phylogenetic relationships among the included taxa were inferred using maximum parsimony and maximum likelihood methods. Penaincisalia sigsiga (Bálint et al), P. cillutincarae (Draudt), P. atymna (Hewitson) and P. loxurina (C. Felder & R. Felder) were easily delimited as the morphological, geographic and molecular data were congruent. Penaincisalia ludovica (Bálint & Wojtusiak) and P. loxurina astillero (Johnson) represent the same entity and constitute a sub-species of P. loxurina. However, incongruence among morphological, genetic, and geographic data is shown in P. chachapoya (Bálint & Wojtusiak) and P. tegulina (Bálint et al). Our results highlight that an integrative approach is needed to clarify the taxonomy of these neotropical taxa, but more genetic and geographical studies are still required.

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Expert survey on priorities for the information society in the Caribbean

An on-line survey of experts was conducted to solicit their views on policy priorities in the area of information and communication technologies (ICT) in the Caribbean. The experts considered the goal to “promote teacher training in the use of ICTs in the classroom” to be the highest priority, followed by goals to “reduce the cost of broadband services” and “promote the use of ICT in emergency and disaster prevention, preparedness and response.” Goals in the areas of cybercrime, e-commerce, egovernment, universal service funds, consumer protection, and on-line privacy rounded out the top 10. Some of the lowest ranked goals were those related to coordinating the management of infrastructure changes. These included the switchover for digital terrestrial television (DTT) and digital FM radio, cloud computing for government ICT, the introduction of satellite-based internet services, and the installation of content distribution networks (CDNs). Initiatives aimed at using ICT to promote specific industries, or specific means of promoting the digital economy, tended toward the centre of the rankings. Thus, a general pattern emerged which elevated the importance of focusing on how ICT is integrated into the broader society, with economic issues a lower priority, and concerns about coordination on infrastructure issues lower still.

Matching of catalogues by probabilistic pattern classification

We consider the statistical problem of catalogue matching from a machine learning perspective with the goal of producing probabilistic outputs, and using all available information. A framework is provided that unifies two existing approaches to producing probabilistic outputs in the literature, one based on combining distribution estimates and the other based on combining probabilistic classifiers. We apply both of these to the problem of matching the HI Parkes All Sky Survey radio catalogue with large positional uncertainties to the much denser SuperCOSMOS catalogue with much smaller positional uncertainties. We demonstrate the utility of probabilistic outputs by a controllable completeness and efficiency trade-off and by identifying objects that have high probability of being rare. Finally, possible biasing effects in the output of these classifiers are also highlighted and discussed.

Batting with occluded vision: An in situ examination of the information pick-up and interceptive skills of high- and low-skilled cricket batsmen

The capability of cricket batsmen of different skill levels to pick-up information from the pre-release movement pattern of the bowler, from pre-bounce ball flight, and from post-bounce ball flight was examined experimentally. Six highly skilled and six low-skilled cricket batsmen batted against three different leg-spin bowlers while wearing liquid crystal spectacles. The spectacles permitted the specific information available to the batsmen on each trial to be manipulated such that vision was either: (i) occluded at a point prior to the point of ball release (thereby only allowing vision of advance information from the bowler's delivery action); (ii) occluded at a point prior to the point of bat[ bounce (thereby permitting the additional vision of pre-bounce ball flight); or (iii) not occluded (thereby permitting the additional vision of post-bounce bat[ flight information). Measurement was made on each trial of both the accuracy of the definitive (forward-backward) foot movements made by the batsmen and their success (or otherwise) in making bat-bat[ contact. The analyses revealed a superior capability of the more skilled players to make use of earlier (pre-bounce) bat[ flight information to guide successful bat-bat[ interception, thus mirroring the greater use of prospective information pick-up by skilled performers observed in other aspects of batting and in other time-constrained performance domains. (c) 2006 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Discovering user access pattern based on probabilistic latent factor model

There has been an increased demand for characterizing user access patterns using web mining techniques since the informative knowledge extracted from web server log files can not only offer benefits for web site structure improvement but also for better understanding of user navigational behavior. In this paper, we present a web usage mining method, which utilize web user usage and page linkage information to capture user access pattern based on Probabilistic Latent Semantic Analysis (PLSA) model. A specific probabilistic model analysis algorithm, EM algorithm, is applied to the integrated usage data to infer the latent semantic factors as well as generate user session clusters for revealing user access patterns. Experiments have been conducted on real world data set to validate the effectiveness of the proposed approach. The results have shown that the presented method is capable of characterizing the latent semantic factors and generating user profile in terms of weighted page vectors, which may reflect the common access interest exhibited by users among same session cluster.

A design pattern for efficient retrieval of large data sets from remote data sources

Retrieving large amounts of information over wide area networks, including the Internet, is problematic due to issues arising from latency of response, lack of direct memory access to data serving resources, and fault tolerance. This paper describes a design pattern for solving the issues of handling results from queries that return large amounts of data. Typically these queries would be made by a client process across a wide area network (or Internet), with one or more middle-tiers, to a relational database residing on a remote server. The solution involves implementing a combination of data retrieval strategies, including the use of iterators for traversing data sets and providing an appropriate level of abstraction to the client, double-buffering of data subsets, multi-threaded data retrieval, and query slicing. This design has recently been implemented and incorporated into the framework of a commercial software product developed at Oracle Corporation.

Introducing uncertainty into pattern discovery in temporal event sequences

Pattern discovery in temporal event sequences is of great importance in many application domains, such as telecommunication network fault analysis. In reality, not every type of event has an accurate timestamp. Some of them, defined as inaccurate events may only have an interval as possible time of occurrence. The existence of inaccurate events may cause uncertainty in event ordering. The traditional support model cannot deal with this uncertainty, which would cause some interesting patterns to be missing. A new concept, precise support, is introduced to evaluate the probability of a pattern contained in a sequence. Based on this new metric, we define the uncertainty model and present an algorithm to discover interesting patterns in the sequence database that has one type of inaccurate event. In our model, the number of types of inaccurate events can be extended to k readily, however, at a cost of increasing computational complexity.

Proceedings of the Eighth Australian and New Zealand Intelligent Information Systems Conference

These are the full proceedings of the conference.